search_articlesSearch eLife — the open-access journal for life sciences & biomedicine — for articles by keyword (gene, disease, method, organism, author, etc.). Returns matching articles with id, title, type, DOI, publication date, authors, and subjects. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 15, max 100). | |
| query | Yes | Search keywords, e.g. "crispr base editing". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by explicitly stating 'Keyless' (no authentication required). This is a useful behavioral trait beyond annotations. No other behavioral details (e.g., pagination, error handling) are provided, but the keyless info is relevant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. The first sentence efficiently conveys the core purpose and return values; the second adds a key behavioral note ('Keyless'). Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple search tool with no output schema and only two parameters, the description is nearly complete. It specifies what is returned (id, title, etc.) and notes keyless access. The schema covers limits and defaults. Minor omission: no default limit stated in description, but it's in schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage: both parameters (limit, query) are described. The description does not add additional semantics beyond restating that search is by keyword. Thus, it meets the baseline without enhancement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Search'), the resource ('eLife articles'), and the purpose ('for articles by keyword'). It specifies the return fields (id, title, type, DOI, etc.), distinguishing it from sibling tools like get_article or latest_articles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via examples and notes 'Keyless' accessibility, but does not explicitly state when to use this tool over siblings (e.g., get_article for a specific article, latest_articles for recent ones). No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose. Tools like ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are differentiated by reliability mode; entity_profile vs compare_entities serve single vs multi-entity; and memorization, subscription, and search tools occupy separate operational niches. No two tools could be easily confused.
Tool names follow no consistent pattern. Some use verb_noun (ask_pipeworx, resolve_entity, validate_claim), others are noun phrases (polymarket_arbitrage, ai_visibility_check), and some mix verb+noun with underscores inconsistently (generate_llms_txt, scan_competitor_ai_presence). This lack of uniformity makes the surface harder to navigate.
34 tools is borderline high. The server spans multiple domains (data query, prediction markets, eLife, memory, subscriptions), and each domain gets several tools, making the overall surface feel bloated. While individual tools are justified, the total count strains discoverability and hints at scope creep.
The tool set is incomplete relative to its stated breadth. For a server named 'Elife', only 3 tools actually serve eLife; the rest are dominated by Pipeworx and Polymarket. Within the query/data domain, coverage is deep but lacks write/modify tools. Prediction market analysis lacks execution tools (no order placement). This leaves clear gaps for agents that need to act on the data.